Method and system for 3d root canal treatment planning

ABSTRACT

A three-dimensional computer model of the patient&#39;s tooth, including the pulp chamber and root canals, is created by combining at least one grey value image of the tooth and/or surface information about at least part of the intra-orally visible part of the tooth with a statistical, parameterized shape model of each tooth type (upper or lower incisors, canines, pre-molars, molars) as the patient&#39;s tooth to be treated. This allows for planning and/or simulation of one or more root canal treatments on the computer model of the patient&#39;s tooth and that the dentist or dental specialist is given qualitative and/or quantitative information by the system in order to aid in adequately analyzing the risks related to performing the root canal treatment with the proposed or user-selected endodontic tools.

The present invention relates to a method and system for 3D root canaltreatment planning as well as software for carrying out such methods.

BACKGROUND

Root canal treatment is a tooth-saving treatment that eliminatesinfections, protects the decontaminated tooth from future infections,and—if needed—restores the tooth at crown level either with or withoutuse of a post. During this treatment the root canals, which mainlycontain the nerve tissue and blood vessels are cleaned, shaped,decontaminated and subsequently filled with an inert filling such asgutta percha. In cases where the remaining tooth structure isinsufficient to support a proper reconstruction of the dental crown, ametal or glass fiber post is positioned in one of the root canals and acore build-up is created in order to support and provide retention forthe prosthetic restoration (i.e. crown).

Root canal treatment can fail or lead to complications due to severalreasons, e.g. insufficient cleaning of the root canals, incompletefilling of the root canals, untreated canals since these were missed bythe practitioner, root perforations or file fracture during shaping ofthe canals, root fractures . . . .

According to literature the use of 3D tooth assessment can reduce therisk of complications during root canal treatment. Cone beam computedtomography (CBCT) for instance can be used in the management ofendodontic problems, i.e. in the assessment of the true size, extent,nature and position of peri-apical and resorptive lesions, in theassessment of root canal anatomy, root fractures, and the nature of thealveolar bone topography around teeth, or in the planning of endodonticsurgery (cf. New dimensions in endodontic imaging: Part 2. Cone beamcomputed tomography. International Endodontic Journal, 42, 463-75,2009). Cone beam computed tomography provides more comprehensivediagnostic data compared to intra-oral radiography, hence resulting inmore accurate diagnosis and monitoring, and therefore improving themanagement of endodontic problems.

Micro-computed tomography (μCT) has been used in academic settings, onextracted teeth for three-dimensional reconstruction and assessment oftooth and root canal morphology for endodontic research purposes (cf. Anapplication framework of three-dimensional reconstruction andmeasurement for endodontic research, Yuan Gao, Ove A. Peters, HongkunWu, Xuedong Zhou, J Endod 2009; 35:269-274). The internal and externalanatomies of the tooth were reconstructed and the dimensions of rootcanal and radicular dentin quantified. The root canal dimensions werecalculated by first defining the root canal middle line and thencalculating the distance from the middle line to the root canal surface.These distances were subsequently visualized by means of a colour-codeon the root canal surface. The minimal distance from the external rootsurface to the root canal surface was also calculated and visualized bymeans of a colour-code. Then the evaluation of the root canalpreparation was performed by registering pre- and post-preparationimages of the tooth. In both image sets the root canal was segmented andvisualized in 3D for a graphic comparison of the change of canal shape,namely the amount of dentin removal during canal preparation. Inaddition the perforation risk during removal of a broken instrumentcould be analysed. After virtually simulating the removal of the saidbroken instrument by means of a user specified trepan/trephine on thecomputer, a thickness analysis on the remaining root was performed, as ameans to quantify the risk of root perforation.

UK patent application, 1108002, Method and system for establishing theshape of the occlusal access cavity in endodontic treatment, describesthe use of a three-dimensional computer model of the tooth including thepulp chamber and the root canals in order to define the optimal shapeand geometry of the occlusal access cavity to the tooth roots prior toroot canal treatment.

While the use of 3D computer images and models has been reported for thepreparation of root canal treatment, the available prior art fails toprovide a method that is usable in the daily clinical practice. CurrentCBCT technology does not provide the required image resolution to allowfor planning of the root canal treatment, since the root canals areoften hardly if at all distinguishable from noise in the images. Even incases where the root canals can be discerned, the reliability ofmeasurements performed on the images, e.g. with respect to the canaldimensions, is insufficient to provide added value when planning theclinical intervention. In addition, radiation doses required for CBCTimaging can drastically exceed those of traditional X-rays, potentiallyadding risk to the patient, and making the technique currently unsuitedfor most endodontic indications. μCT imaging is even less suitable:currently, there is no commercially available equipment for acquiringμCT images on patients, since fields of view are too limited, requiredradiation doses too high and data acquisition times too long with thistechnology. μCT imaging currently only works on extracted teeth, inspecific set-ups for research purposes.

SUMMARY OF THE INVENTION

An object of the present invention is to provide a method and system for3D root canal treatment planning. Embodiments of the present inventionaim to overcome one or more of the problems described above and toprovide a method and system that aids the dentist or dental specialistin more accurately planning primary root canal treatment and/or rootcanal retreatment. An aspect of the present invention is the use ofsimulation to provide a qualitative and/or quantitative assessment oftreatment related risks.

A significant advantage of embodiments of the current invention is thatcase or patient specific planning can be performed in 3D without theneed for 3D imaging techniques exposing patient to radiation doseshigher than conventional X-ray, while still providing detailedinformation about the anatomical characteristics of the teeth.

Another aspect of the current invention is that a three-dimensionalcomputer model of the patient's tooth, including the pulp chamber androot canals, is created by combining at least one 2D grey value image ofsaid tooth and/or surface information about at least part of theintra-orally visible part of the tooth with a statistical, parameterizedshape model of each tooth type (upper or lower incisors, canines,pre-molars, molars) as the patient's tooth to be treated.

Yet another aspect of the current invention is that the method andsystem allows for planning and/or simulation of one or more root canaltreatments on the 3D computer model of the patient's tooth and that thedentist or dental specialist is given qualitative and/or quantitativeinformation by the system in order to aid in adequately analysing therisks related to performing the root canal treatment with the proposedor user-selected endodontic tools.

It is therefore a significant advantage of the current invention that itaids the dentist or dental specialist in selecting the optimal tools forperforming a root canal treatment prior to the treatment itself.

These and further objects, features and advantages of the invention willbecome apparent from the following detailed description whereinreference is made to the figures in the accompanying drawings.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a flowchart visualizing the input and the different stepsof the method for 3D root canal treatment planning according to anembodiment of the present invention;

FIG. 2 shows a system and software for 3D root canal treatment planningaccording to an embodiment of the present invention;

FIG. 3 shows an example of 2D grey value image of patient's tooth;

FIG. 4 shows an example of 3D surface information of intra-orallyvisible part of patient's tooth, obtained by optically scanning theplaster model of the patient's dentition;

FIG. 5 shows an example of 3D model of patient's tooth including pulpchamber and root canals.

DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention will be described with respect to particularembodiments and with reference to certain drawings but the invention isnot limited thereto but only by the claims.

According to a preferred embodiment of the invention a first stepaccording to a method for simulating root canal treatment simulationconsists in creating and visualizing a three-dimensional model of apatient's tooth including the pulp chamber and the root canals.Therefore, the system consists at least of a computer including computerprograms which can be utilized with the method for visualizing saidthree-dimensional model.

With reference to FIGS. 3 to 5, according to one embodiment the 3D modelof the tooth with pulp chamber and root canals is generated based on thecombination of 3D imaging data of the crown and one or more 2Dradiographs of the tooth. Therefore the 3D crown information of therespective tooth is digitized. This can be done using different methods.A first method uses a conventional impression of the patient's teeth.This negative impression is used for making a positive impression, e.g.by pouring a model using plaster or other suitable material, whose 3Dsurface is then captured and digitised, e.g. scanned either optically orby CT techniques (e.g. μCT scanner, CBCT scanner . . . ). Alternatively,the negative impression itself is used to obtain the 3D surface details,e.g. the impression is scanned. In a second method the crown of thetooth is digitized by taking an intra-oral scan of the respective tooth.In a third method 3D imaging data collected during a volumetric scansuch as with a CBCT scanner exam is used.

The digital crown information is combined with the 2D radiographs bymeans of an expert system in order to construct a 3D model of the toothincluding the pulp chamber and the root canals. The expert systempreferably includes a statistical shape model in order to calculate the3D model of the tooth as accurately as reasonably possible based on the2D radiograph data combined with the 3D crown data. The statisticalshape model is preferably generated for each type of tooth separately.It can comprise at least a parameterized 3D (volumetric or surface)representation of the tooth, potentially extended with associatedparameterized 2D radiographs. Variances in the 3D representation arelinked to associated variances in the 2D radiographs. Examples of suchvariances are tooth morphology, variation in number of cuspids,variation in size and shape of the pulp chamber, number of roots androot canals, variation in size and shape of root canals . . . . Thetechnique used to combine one or multiple 2D images with a statisticalshape model in order to calculate a patient specific 3D model may forinstance consist in calculating the projection outlines (e.g. 2D curves)of the statistical shape model in planes estimated to correspond to theprojection planes of the 2D images. In the 2D images, the edges of thetooth are calculated (e.g. by means of edge detection algorithms). The3D statistical shape model is next modified (using previously mentionedparameter values) and repositioned relative to the coordinate systemdefined by the 2D images, all the while reassessing the outlines, untilthe outlines of the 3D model match (according to a predefined criterion)the edges calculated on the 2D images. The resulting modified 3Dstatistical shape model is then used as 3D model for the specific case.

Alternatively, if the covariances between the statistical shape modeland its corresponding parameterized 2D radiographs are known, it may besufficient to modify the 2D radiographs associated with the statisticalshape model by varying the parameter values dictating its variances, tomatch the 2D radiographs obtained in the mouth of the patient, in orderto directly obtain the desired corresponding 3D model of the tooth (i.e.external geometry, shape and location of the pulp chamber and toothroots).

The above-described methods can be applied for generating accurate 3Dmodels of individual teeth either for primary root canal treatment orretreatment.

Once the tooth and root canals are visualized in 3D, the next stepsaccording to a method for 3D root canal treatment planning can start;i.e. planning and/or simulation of the root canal treatment andcalculating feedback to aid in the determination of the optimal way togo about the treatment. These next steps can be performed in anyarbitrary order and are not limited by the following examples.

According to a first illustrative example, the system allows forplanning the root canal treatment by determining an optimal filesequence (i.e. diameter of files and their working length) for reaming aroot canal. Therefore the system allows for defining the midlines of theroot canals either manually or (semi-)automatically. In a manualapproach the user has to scroll through parallel 2D sectional images(axial, bucco-lingual or mesio-distal) and draw a line sequence or acurve (e.g. polynomial or spline) by manually indicating succeedingcentre points of the root canal within the 2D sectional images. In asemi-automatic approach the user starts with selecting a root canal byfor instance indicating apical and occlusal end of the root canal, or bymarking the surface of the root canal, or by any other method.Subsequently, an algorithm defines a number of equidistant parallelsections (e.g. axial, or bucco-lingual, or mesio-distal) in which thecontour of the root canal (i.e. the intersection curve of the root canalsurface and the 2D plane defining the section) is calculated as well asthe centre point of this contour. The centre point can be calculated indifferent ways; e.g. as the centre of gravity of the surface delineatedby the contour of the root canal, or as the centre of the largestinscribed circle of the root canal contour, or as the centre of thesmallest circumscribed circle of the root canal contour, or as thecentre of the best fitting ellipse/circle of the root canal contour, orby yet another method. Calculating a curve through these centre points,results in a midline for the root canal. According to another approachthe midline can be improved by determining the contours and their centrepoints of the root canal in multiple orthogonal sections and determiningthe best fitting curve through all the resulting centre points.According to yet another approach the midline determined based on one ofthe above described approaches (i.e. by means of parallel equidistant 2Dsections) can be iteratively improved by defining sections perpendicularto this midline at equal distances along this midline, determining thecontour of the root canal and its centre point in these new 2D sections,and defining a new curve through these new centre points. This methodcan be repeated several times in order to obtain an accurate descriptionof the midline of the root canal.

Based on the midline for each root canal new sectional imagesperpendicular to this midline and at equal distances along this midlinecan be generated and visualized. Within these 2D sections the minimalcircle circumscribing the contour of the root canal can be calculatedautomatically and its diameter—optionally increased with a predefinedconstant value—used to determine the minimal diameter of the file neededfor reaming the root canal in that section. Based on this succession ofdiameter values along the root canal a sequence of best fitting filesfor reaming each individual root canal is determined. A first method isby outlining the minimal diameter values for the file for the succeedingsections along a straight line at the distances of the respectivesections and calculating the smallest cone that circumscribes thesediameter values. A set of files, available through a library, is fittedin this cone at maximum depth (i.e. until the file makes contact withthe cone). Then the difference between this cone volume and the totalvolume by combining all files is calculated in order to quantify thereaming of the root canal by using this sequence of files. In order toimprove the reaming of the root canal the files can be positioned deeperthan at maximum depth. The increase in depth position for each file caneither be a fixed predefined distance or be calculated to completelycover the circumscribed cone volume but with a minimal additional volumeremoval, or be calculated to completely cover the circumscribed conevolume but with a predefined limited sequence of files. The result is asequence of files with the corresponding depth to which each file mustbe used (working length). According to a second method a file ismodelled using its 3D CAD/CAM information and fitted—simulatingnecessary bending of the file corresponding with the 3D curvature of theroot canal—into the root canal to maximal depth, which will depend onthe size of the file and the size of the root canal. This fitting actionis repeated for files with increasing diameter, and as such a sequenceof files and their working length is determined for reaming the rootcanal. Similar to the first method the maximal depth of a file can alsobe increased with either a predefined fixed value or be calculated inorder to either optimize the reaming of the root canal or limit thenumber of files necessary for reaming the root canal. In this 3Dapproach the optimization of the root canal reaming is done by comparingthe volume reamed by the file sequence with the real root canal volume.The reaming is optimal if the root canal volume is completely reamedwith a minimal reaming of additional root material. According to apreferential implementation, material properties of the endodonticinstruments (e.g. files) are used during the simulation of the bendingto calculate and visualize (e.g. by means of a color code—green=low;orange=moderate; red=high) the risk of instrument fracture.

According to a preferred step of the current invention the system allowsfor quantitative and/or qualitative feedback in order to aid inadequately analyzing the risks related to performing the root canaltreatment.

As a first example the system can allow for visualizing the wallthickness of the root along the root canal to provide feedback regardingfor instance the risk of root fracture or root perforations during rootcanal treatment. Therefore the distance between the surface of the rootcanal and the external surface of the tooth/tooth root is calculated.Given that a triangulated surface representation may be used tovisualize the different anatomical structures (crown, tooth root; rootcanal, pulp chamber, etc.) the distance can be determined in differentways. A first method is by calculating the distance between each node oftriangles on the outer root surface and the closest point on the rootcanal surface. A second method is by calculating the distance betweeneach node on the root canal surface and the closest point on the outerroot surface. A third method is by calculating the distance from eachnode on the root surface along its normal to the root canal surface. Anyother method for distance calculation can be used. These numericalvalues can be visualized for instance by means of a colour code on the3D model or in the 2D sections in order to provide the user thenecessary graphical feedback regarding the thickness of the root alongthe root canal. Other methods for visualizing numerical values areisometric lines either on the 3D surface or in the 2D sections, orlabelling.

Another valuable parameter is the distance from each point of the rootcanal surface to the outer root surface but calculated along thecorresponding radial direction within the plane perpendicular to themidline of the root canal. This value, or this value reduced with asafety value specifying the minimally desired remaining root wallthickness, gives the user feedback regarding the maximally allowableincrease of the file diameter for the root canal treatment. These valuescan also be shown on the tooth model by means of a colour coding. Incase the safety value for the minimal wall thickness is specified, thenthe parts of the roots with a smaller thickness can also be marked. Thislatter method gives the user feedback regarding the possible increase offile size in each section without risk for perforation of the root.

Yet another parameter that gives valuable feedback to the user is thecurvature of the root canal since this determines the necessary bendingof the files during treatment and as such the risk of instrumentfracture. The curvature of the root canal can be determined bycalculating the curvature of the midline of the root canal in each pointof the root canal. This value can be visualized as well by a colour codealong the root canal. This value can be compared with the maximalallowable bending of the files that will be used during treatment and assuch critical areas (i.e. areas with risk of fracture of the file due tobending exceeding the maximal allowable bending of the endodontic file)can be marked for the user.

According to another step of the current invention, the system allowsfor simulating the root canal treatment.

An example of root canal treatment simulation is the cleaning of a rootcanal (i.e. either primary root canal treatment or retreatment). Thismeans that the file sequence as proposed by the system or as specifiedby the user is applied to the respective root canal and the materialremoved by the file is removed from the tooth model. As such a 3D modelof the post-treatment tooth is created. This post-treatment model can becompared with the pre-treatment model and the removed material can bemarked visually either in the 3D model or in the 2D slices. Additionallythe volume of the reamed root canal can be calculated in order toquantify the volume that needs to be filled, and as such provide ameasure for the necessary quantity of filling material needed duringroot canal treatment. Another feature of the system is that multipledifferent treatments can be simulated and the difference between thesetreatments can be visualized in a similar way as the difference betweenpre- and post-treatment. This will aid in selecting the optimal cleaningtreatment for a specific case.

Another example of root canal treatment simulation is the planning ofthe endodontic post to provide retention for the prosthetic restorationin cases where there is insufficient remaining tooth structure to retainthe core. In a first approach the user can select a post from a libraryof (glass fiber or metal) posts and place it virtually in the rootcanal, According to another approach a post is automatically selectedfrom a library of posts based on one (or a combination) of the followingcriteria: post with dimensions that best fit the dimensions of thereamed root canal, post with dimensions that minimally circumscribes thereamed root canal, post with dimensions that ensures a minimal root wallthickness around the post, post with dimensions that limits the risk oftooth fracture or . . . .

After placing the post it is possible to determine perforations—ifany—by determining the intersections between the post and the 3D toothmodel. These intersections can be visualized by colour marking eitherthe part of the surface of the post that is outside the tooth model orthe intersection lines between post and tooth model. After virtuallyplacing the post it is also possible to visualize the root thicknessaround the post in order to give the user feedback with respect toeither the risk of perforation or the risk of fracture of the tooth root(as a result of the weakening of the tooth due to the post preparation).The same technical methods as described for calculating the rootthickness along the root canal can be used for calculating the rootthickness around the post. The risk of perforation can be quantifiedbased on threshold values for the root thickness that are clinicallyaccepted. Another way of quantifying the risk of perforation is bytaking into account on the one hand the root thickness around the postand on the other hand the clinical deviations in preparing the cavityfor the posts (i.e. the deviations between the planned position andorientation of the post and the actual position and orientation). Themain cause of these deviations is the limitation of the operator intransferring the planning to the patient, which is also due to thelimitations of the instrumentation used. Another method for quantifyingthe risk of perforations is by using a statistical model obtained byretrospectively analyzing a large number of tooth-root preparations forpost placement including those with and without perforations. The riskof fracture can be quantified by including a mechanical strengthanalysis of the prepared tooth root (e.g. simplified mechanical model orfinite element model). Another way of quantifying the risk of fractureis by means of applying a statistical model. Such a statistical modelwill include besides the root thickness around the post a number ofother parameters like bite forces, gender, tooth type or size . . . forpredicting the fracture risk.

According to yet another example the planning software also aids indetermining the dimensions of the core build-up to replace the missingtooth material in order to strengthen the tooth to prevent breakage.Therefore, either an expert system is set up to propose an ideal corebuild-up or tools are provided to the user for manually creating a corebuild-up and allowing to perform an analysis for verifying for examplethe resulting tooth strength, the chances for a successful crownrestoration . . . . For the latter the planning software will also needto allow the user to create the crown restoration, either by importing awax-up, or by selecting, positioning, and if needed adapting a crownfrom a library of crowns, or by mirroring the patient's contra-lateralcrown, or by using a statistical model for fitting a crown in betweenthe neighbouring teeth, or by any other possible method. Feedback canthen be given to the user with respect to the available thickness forthe restorative crown in order to estimate the risk of fracture of thecrown or possibly crown perforations. As such the post selection andpositioning, and the core build-up can be optimized prior to the rootcanal treatment in order to reduce clinical risks or failure within thepatient. According to another preferential implementation, the remaininginformation of the tooth/tooth root is compared against a parameterized3D statistical model of the relevant tooth type. The statistical modelof the tooth is aligned with and modified according to a best fit withsaid remaining part of the tooth/tooth root. The missing informationrequired to perform the prosthetic restoration (e.g. information of thecrown) is given as the difference between the remaining tooth and themodified statistical model.

The ideal post could also be automatically selected from a library andautomatically positioned in the 3D model of the tooth. Therefore anexpert system is set up that takes into account all necessary parameters(e.g. root anatomy, restorative crown, strength of tooth with post . . .) in order to propose a clinically relevant size and position for thepost for each individual case. This expert system can either consist ofa set of clinically applied rules or be a statistical model generated bya retrospective analysis of successful cases, or any type of heuristic.

All methods according to embodiments of the present invention andsystems according to the present invention can be implemented oncomputer equipment 30 that is adapted to implement methods of thepresent invention. A schematic representation of such a computer system30 is shown in FIG. 2 which includes a computer 31 with a processor 32and memory and preferably a display. Such methods can be based on thecomputer 31 having means for generating and visualizing a 3D model, e.g.including the pulp chamber and root canals, of the tooth to be treated,Such a method can be implemented on a computer 31 by providing softwarethat when run on the computer allows the combination of at least onepiece of tooth specific digital information, e.g. 2D grey value image ofa patient's tooth 35, and/or a 3D surface information of a patient'stooth 36 with a statistical, parameterized shape model of each toothtype obtained by module 41. The tooth type can be upper or lowerincisors, canines, pre-molars, or molars. For achieving this, an inputdevice is provided for inputting data for the 3D model, e.g. from astorage device such as a CD-ROM, or solid state memory or via a networklink, e.g. via a LAN or WAN.

The method can be implemented on a computer 31 by providing software 33,e.g. as module 36 that when run on a computer allows planning and/orsimulating the root canal treatment on the generated 3D model of thetooth. The software is adapted such that when run on a computer it has amodule 43 which allows providing qualitative and/or quantitativefeedback relative about the effect of the planned/simulated treatment onthe 3D model. It also allows selecting or determining of an approach,e.g. the best approach to the root canal treatment. The computer systemcan comprise an expert system set up to propose an ideal treatment suchas a core build-up or tools 42 are provided to the user for manuallycreating a core build-up and allowing to perform an analysis forverifying the treatment.

The computer 31 can comprise a processor 32 and a memory 34, 40 whichstores machine-readable instructions (software as described above)which, when executed by the processor cause the processor to perform thedescribed methods—A computing system which can be utilized with themethods of the present invention may run computer programs such as3-Matic™ as supplied by Materialise N.V., Leuven, Belgium. The computermay include a video display terminal, a data input means such as akeyboard, and a graphic user interface indicating means such as a mouse.The computer may be implemented as a general purpose computer, e.g. aUNIX workstation or a personal computer.

The computer 31 typically includes a Central Processing Unit (“CPU”),such as a conventional microprocessor of which a Pentium processorsupplied by Intel Corp. USA is only an example, and a number of otherunits interconnected via bus system. The bus system may be any suitablebus system. The computer includes at least one memory. Memory mayinclude any of a variety of data storage devices known to the skilledperson such as random-access memory (“RAM”), read-only memory (“ROM”),and non-volatile read/write memory such as a hard disc as known to theskilled person. For example, the computer may further includerandom-access memory (“RAM”), read-only memory (“ROM”), as well as adisplay adapter for connecting the system bus to a video displayterminal, and an optional input/output (I/O) adapter for connectingperipheral devices (e.g., disk and tape drives) to the system bus. Thevideo display terminal can be the visual output of computer, and can beany suitable display device such as a CRT-based video display well-knownin the art of computer hardware. However, with a desk-top computer, aportable or a notebook-based computer, the video display terminal can bereplaced with a LCD-based or a gas plasma-based flat panel display. Thecomputer further includes an user interface adapter for connecting akeyboard, mouse, and optional speaker.

The computer can also include a graphical user interface that resideswithin machine-readable media to direct the operation of the computer.Any suitable machine-readable media may retain the graphical userinterface, such as a random access memory (RAM), a read-only memory(ROM), a magnetic diskette, magnetic tape, or optical disk (the lastthree being located in disk and tape drives). Any suitable operatingsystem and associated graphical user interface (e.g., Microsoft Windows,Linux) may direct CPU. In addition, computer includes a control programthat resides within computer memory storage. Control program containsinstructions that when executed on CPU allow the computer to carry outthe operations described with respect to any of the methods of thepresent invention.

The graphical user interface is used to visualize the 3D model,including the pulp chamber and root canals, of the tooth to be treated.It can also be used for planning and/or simulating the root canaltreatment on the generated 3D model of the tooth. It can also be usedfor visualising qualitative and/or quantitative feedback relative aboutthe effect of the planned/simulated treatment on the 3D model and it canalso be used for visualizing the selecting or determining of an approachor the best approach to the root canal treatment.

Those skilled in the art will appreciate that other peripheral devicessuch as optical disk media, audio adapters, or chip programming devices,such as PAL or EPROM programming devices well-known in the art ofcomputer hardware, and the like may be utilized in addition to or inplace of the hardware already described.

The computer program product for carrying out the method of the presentinvention can reside in any suitable memory and the present inventionapplies equally regardless of the particular type of signal bearingmedia used to actually store the computer program product. Examples ofcomputer readable signal bearing media include: recordable type mediasuch as floppy disks and CD ROMs, solid state memories, tape storagedevices, magnetic disks.

Accordingly, the present invention also includes a software productwhich when executed on a suitable computing device carries out any ofthe methods of the present invention. Suitable software can be obtainedby programming in a suitable high level language such as C and compilingon a suitable compiler for the target computer processor, Such methodswill now be described.

According to step 100 of the method, a 2D grey value image is taken ofthe patient's tooth; 3D surface information of the intra-orally visiblepart of the patient's tooth is digitized; and a statistical,parameterized shape model of the respective tooth (e.g. incisor, canine,premolar, or molar) is made available.

At step 101 all data is loaded into a computer—such as computer 31above, Computer 31 is adapted to carry out any of the methods of thepresent invention.

At step 102 the 2D and 3D information of the patient's tooth is combinedwith the statistical, parameterized shape model by means of a dedicatedsoftware application, i.e. as run on computer 31. This softwareapplication can operate either fully automatically or semi-automatically(i.e. requiring user input at well defined steps of the algorithm), Theuse of a statistical, parameterized shape model (also known as an activeshape model) in combination with 2D grey value images or 3D surfaceinformation is known and described in literature for variousapplications (Nonrigid 3-D/2-D registration of images using statisticalmodels. In: MICCAI. Volumes LNCS 1679, 138-147, 1999; Biogeneric tooth:a new mathematical representation for tooth morphology in lower firstmolars. Eur Oral Sci 113, 333-340, 2005; Registration algorithm forstatistical bone shape reconstruction from radiographs—an accuracystudy, Proceedings of the 29^(th) Annual International Conference of theIEEE Engineering in Medicine and Biology Society, 6375-6378, 2007;Evaluation and enhancement of a procedure for generating 3D bone modelusing radiographs, Advances in Medical Engineering, Proceedings inPhysics 114, 163-168, 2007; 2D/3D deformable registration using a hybridatlas. In: MICCAI. Volume LNCS 3750, 223-230, 2005). A parameterizedstatistical shape model of a tooth including the internal geometry (i.e.pulp chamber and root canals) can be obtained as follows.

A large set of natural human teeth of a certain tooth type (incisors,canines, premolars, or molars) is digitized in order to obtain athree-dimensional description of both the outer shape (crown and root)and the internal shape (pulp chamber and root canals). Digitizing theseteeth can be done for example by taken μCT scans of the teeth, which arethen processed by a software program such as SimPlant™ supplied byMaterialise Dental, Leuven, Belgium in order to generate digitalthree-dimensional descriptions of the internal and external shape ofthese teeth. The three-dimensional description of the tooth can be asurface model, a set of anatomical landmarks/points characterizing thetooth shape, a volumetric model or yet any other 3D representationdetailing the internal and external shape of the tooth. The selected setof natural human teeth must be a representative sample of the populationfor which the parameterized statistical shape model will be used. Thus,this set of natural human teeth must reflect the natural variations inexternal and internal three-dimensional shape of that type of humantooth within the population of interest.

First a coordinate reference is established for the digitized set ofnatural teeth in order to align all teeth, which means that position,scale and rotational effects are filtered out. Now the variation inshapes within this coordinate reference for the set of natural teeth canbe analysed and described. One example for describing the variation inshapes is by means of principal components. Therefore a principalcomponent analysis is performed on the set of aligned natural humanteeth, which is in fact a statistical analysis resulting in eigenvectorsand eigenvalues. These eigenvectors (or principal components) areuncorrelated variables/parameters describing the variation in shapes.The eigenvectors are ordered by their eigenvalue, highest to lowest, togive the components in order of significance. The eigenvector with thehighest eigenvalue describes the largest variation in shape. Theparameterized statistical model/description of the three-dimensionalshape of the tooth (including internal pulp chamber and root canals) isin fact the linear combination of either all these eigenvectors or a setof these eigenvectors (i.e. leaving out the eigenvectors of lessersignificance, thus with low eigenvalues), Varying the parameter values(i.e. the values with which the eigenvectors are multiplied) in thestatistical model changes its three-dimensional shape and allows for itto be brought into exact correspondence (in terms of shape and geometry)with the 3D description of any tooth used in the initial analysis usedto create the statistical model in case the statistical shape model isbased on all eigenvectors. When only using a subset of the eigenvectorsthe correspondence will not be exact but a good approximation will beobtained since only eigenvectors of lesser significance are not added tothe statistical shape model. In addition, the parameters can be used tobring the statistical model into approximate correspondence to any toothof the same type but foreign to the original set of teeth used to createthe statistical model. The better the set of natural human teeth used tocreate the parameterized statistical model reflects all shape variationsin human teeth, the more accurate the statistical shape model can bebrought into correspondence to any new example of such a tooth.

In an approach according to an embodiment of the present invention theparameterized statistical model is used in combination with 3D crownsurface information (i.e. intra-orally visible part) and one or more 2Dgrey value images of a patient's tooth. The aim is to create athree-dimensional representation of this patient's tooth by means ofcombining the patient specific information with the parameterized,statistical shape model in such a manner that the result approximates aswell as possible the real anatomy of the tooth as present in thepatient's mouth. Therefore, at first the patient specific toothinformation (3D crown surface and 2D grey value images) is aligned withthe parameterized statistical shape model, which means that allavailable data is positioned within a same coordinate system. Then theparameter values of the statistical shape model are iteratively changedin order to modify its shape and geometry in order to match with on theone hand the 3D crown information and with on the other hand the 2D greyvalue image(s) and this according to a predefined criterion. Thecriterion for the fitting on the 3D crown information can be minimizingthe distance between the statistical shape model at crown level and the3D crown information. The criterion for the fitting on the 2D grey valueimage(s) can be minimizing the distance between the projection outlinesof the internal and external shape of the tooth of the statistical shapemodel in planes estimated to correspond to the projection plane(s) ofthe 2D grey value image(s). These criterions must be combined in orderto obtain the best fitting 3D description of the patient's tooth thatreflects the internal and external shape with sufficient detail andaccuracy.

Another approach according to an embodiment of the present invention forobtaining a parameterized statistical shape model of a tooth includingthe internal geometry (i.e. pulp chamber and root canals) is thefollowing. In addition to digitizing the set of natural human teeth inorder to obtain a 3D description (same as mentioned above) 2D grey valueimage(s) can be taken of these teeth and digitized. The combined 2d and3D data of each tooth within the set can be analyzed statistically inorder to obtain a parameterized shape model including a 3D shape modeland an associated parameterized 2D grey value image(s), in which certaincomponents/parameters of the shape model are directly linked toparameters of the 2D grey value image(s). As such the covariancesbetween the statistical shape model and its corresponding parameterized2D grey value image(s) are known. Fitting this parameterized statisticalshape model onto the 2D grey value images of the patient's tooth can bedone by iteratively modifying parameters of the parameterized 2D greyvalue image(s), which will result in a corresponding modification of the3D shape model, until a good match is obtained. This can further becombined with matching the parameterized statistical shape model ontothe 3D crown information of the patient's tooth. As such a 3D model ofthe patient's tooth is obtained that includes external geometry, shapeand location of the pulp chamber and root canals.

The result is a detailed 3D model of the patient's tooth including a 3Drepresentation of the pulp chamber and root canals, which is visualizedat step 103. Different visualization modes, such as for example 3Dsurface renderings, sectional images, transparency mode, volumerenderings . . . can be made available through the software applicationin order to allow the dentist or dental specialist to fully assess thethree-dimensional complexity of the root canals and pulp chamber.

At step 104 planning and/or simulation of root canal treatment is doneby means of the software application. This step may include the use ofsoftware tools in combination with a digital library of root canaltreatment tools (e.g. endodontic files, endodontic posts . . . ).

At step 105 qualitative and/or quantitative information is provided tothe dentist or dental specialist about the root canal treatment risk.Different visualization modes, such as for example equidistant lines,colour bands, histograms . . . , can be included in the softwareapplication to clearly present the qualitative and/or quantitativefeedback to the dentist or dental specialist. This allows the dentist ordental specialist to analyse risks related to the simulated root canaltreatment.

At step 106 optimal tools or root canal treatment is selected.

1. A method for 3D planning of the restoration of a tooth comprising thesteps of: generating and visualizing a 3D model of the tooth to berestored by combining at least one piece of tooth specific digitalinformation with a statistical, parameterized shape model of therelevant tooth type, wherein the 3D model includes the root canals andpulp chamber; planning or simulating a root canal treatment on thegenerated 3D model of the tooth creating a post-treatment 3D model ofthe tooth; allowing determining the dimensions of a core build-up toreplace missing tooth material in the post-treatment 3D model in orderto strengthen the tooth to prevent breakage; creating a crownrestoration on the post-treatment 3D tooth model by importing a wax-upor by selecting, positioning, and adapting a crown from a library ofcrowns in the post-treatment 3D model of the tooth, or by mirroring theexisting contra-lateral crown of the patient, or by using a statisticalmodel for fitting a crown in between the neighboring teeth of the toothto be restored; creating a visualization on the post-treatment 3D modelof the tooth of a quantitative feedback of the available thickness ofthe remaining material of the tooth for the restorative crown andestimate the risk of fracture of the crown or possible crownperforations; and selecting or determining an optimal core build-up andsequence of treatment steps for the crown restoration for ensuring toothstrength and successful crown restoration.
 2. The method of claim 1,wherein the step of allowing determining the dimensions of a corebuild-up to replace missing tooth material in the post-treatment 3Dmodel in order to strengthen the tooth to prevent breakage comprisesproviding automatically an ideal core-build up.
 3. The method of claim1, wherein the step of allowing determining the dimensions of a corebuild-up to replace missing tooth material in the post-treatment 3Dmodel in order to strengthen the tooth to prevent breakage comprisesproviding tools for the user for manually creating a core build up. 4.The method of claim 1, comprising the further steps of: allowingselecting of a post to provide retention for the crown restoration froma library of posts and positioning it in the reamed root canal of thepost-treatment 3D model of the tooth; creating a visualization on thepost-treatment 3D model of the tooth of a quantitative feedback on therisk of perforation or the risk of fracture of the tooth root as aresult of the post positioning; and selecting or determining the optimalpost and post position in order to reduce clinical risks or failure ofthe crown restoration, wherein this step develops a sequence oftreatment steps for the preparation of the cavity and root canal for thepost.
 5. The method of claim 4, wherein the post is automaticallyselected from a library of posts based on one or a combination of thefollowing criteria: post with dimensions that best fit the dimensions ofthe reamed root canal of the post-treatment 3D tooth model, post withdimensions that minimally circumscribes the reamed root canal of thepost-treatment 3D tooth model, post with dimensions that ensures aminimal root wall thickness around the post, post with dimensions thatlimits the risk of tooth fracture.
 6. The method of claim 4, wherein thepost is manually selected from a library of posts.
 7. The method ofclaim 4, wherein the post is automatically positioned in thepost-treatment 3D model of the tooth.
 8. The method of claim 4, whereinthe post is manually positioned in the post-treatment 3D model of thetooth.
 9. The method of claim 4, wherein the visualization on thepost-treatment 3D model of the tooth of a quantitative feedback on therisk of perforation or the risk of fracture of the tooth root as aresult of the post positioning comprises a visualization of theintersections between the post and the post-treatment 3D tooth model bycolor marking either the part of the surface of the post that is outsidethe post-treatment 3D tooth model or the intersection lines between thepost and the post-treatment 3D tooth model.
 10. The method of claim 5,wherein the visualization on the post-treatment 3D model of the tooth ofa quantitative feedback on the risk of perforation or the risk offracture of the tooth root as a result of the post positioning comprisesa visualization of the root thickness around the post; and wherein therisk of perforation is quantified based on clinically accepted thresholdvalues for the root thickness around the post.
 11. The method of claim4, wherein the risk of perforation is quantified by using a statisticalmodel.
 12. The method of claim 1, wherein the 3D model is obtained from2D grey value image(s) of patient's tooth and 3D surface information ofan intra-orally visible part of patient's tooth.
 13. The methodaccording to claim 12 wherein the 2D grey value image(s), 3D surfaceinformation and statistical, parametrized shape model of each tooth typeare loaded in a computer.
 14. The method of claim 5, wherein the risk ofperforation is quantified by using a statistical model.
 15. The methodof claim 6, wherein the risk of perforation is quantified by using astatistical model.
 16. The method of claim 7, wherein the risk ofperforation is quantified by using a statistical model.
 17. The methodof claim 2, wherein the 3D model is obtained from 2D grey value image(s)of patient's tooth and 3D surface information of an intra-orally visiblepart of patient's tooth.
 18. The method of claim 2, further comprisingthe steps of: allowing selecting of a post to provide retention for thecrown restoration from a library of posts and positioning it in thereamed root canal of the post-treatment 3D model of the tooth; creatinga visualization on the post-treatment 3D model of the tooth of aquantitative feedback on the risk of perforation or the risk of fractureof the tooth root as a result of the post positioning; and selecting ordetermining the optimal post and post position in order to reduceclinical risks or failure of the crown restoration, wherein this stepdevelops a sequence of treatment steps for the preparation of the cavityand root canal for the post.
 19. The method of claim 3, furthercomprising the steps of: allowing selecting of a post to provideretention for the crown restoration from a library of posts andpositioning it in the reamed root canal of the post-treatment 3D modelof the tooth; creating a visualization on the post-treatment 3D model ofthe tooth of a quantitative feedback on the risk of perforation or therisk of fracture of the tooth root as a result of the post positioning;and selecting or determining the optimal post and post position in orderto reduce clinical risks or failure of the crown restoration, whereinthis step develops a sequence of treatment steps for the preparation ofthe cavity and root canal for the post.
 20. A non-transitory storagemedium storing a computer program product which when executed on acomputer causes the computer to perform a method for 3D planning of therestoration of a tooth comprising the steps of: generating andvisualizing a 3D model of the tooth to be restored by combining at leastone piece of tooth specific digital information with a statistical,parameterized shape model of the relevant tooth type, wherein the 3Dmodel includes the root canals and pulp chamber; planning or simulatinga root canal treatment on the generated 3D model of the tooth creating apost-treatment 3D model of the tooth; allowing determining thedimensions of a core build-up to replace missing tooth material in thepost-treatment 3D model in order to strengthen the tooth to preventbreakage; creating a crown restoration on the post-treatment 3D toothmodel by importing a wax-up or by selecting, positioning, and adapting acrown from a library of crowns in the post-treatment 3D model of thetooth, or by mirroring the existing contra-lateral crown of the patient,or by using a statistical model for fitting a crown in between theneighboring teeth of the tooth to be restored; creating a visualizationon the post-treatment 3D model of the tooth of a quantitative feedbackof the available thickness of the remaining material of the tooth forthe restorative crown and estimate the risk of fracture of the crown orpossible crown perforations; and selecting or determining an optimalcore build-up and sequence of treatment steps for the crown restorationfor ensuring tooth strength and successful crown restoration.